![]() ![]() Their results showed that the two systems had similar performance when extracting vital signs under ambient light conditions. ![]() evaluated the performance of stepped-frequency CW radar and imaging photoplethysmography systems for remote vital-sign detection. The authors in investigated the use of millimeter-wave FMCW radar to remotely monitor vital signs by employing advanced phase unwrapping manipulation, which is a unique method for extracting the vital signs of a subject lying down on a bed. Their algorithm only needed to extract fundamental and second-harmonic components to estimate vital signs. introduced a harmonic multiple-loop detection algorithm for the noncontact detection of vital signs using IR-UWB radar. proposed the first valley peak of the energy function of the intrinsic two-layer mode-function-based ensemble empirical mode decomposition method to simultaneously extract heartbeat and breath information. ![]() The performance of the proposed model was confirmed for long-term data, including static and dynamic conditions, and it is expected to be used for health management through vital-sign monitoring in the home environment. ![]() The average mean absolute errors for RR and HR were 2.67 and 4.78, respectively. From 30 recordings measured during night-time sleep, 10 were used for training, 5 for validation, and 15 for testing. The 1D signal of the selected UWB channel index and the 2D signal applied with the continuous wavelet transform are entered as inputs into the convolutional neural-network-based model that then estimates RR and HR. The clutter is removed from the measured radar signal, and the position of the subject is detected using the standard deviation of each radar signal channel. To this end, we developed and evaluated a deep learning framework that estimates the respiration rate (RR) and heart rate (HR) in real time from long-term data measured during sleep using a contactless impulse radio ultrawide-band (IR-UWB) radar. Vital signs provide important biometric information for managing health and disease, and it is important to monitor them for a long time in a daily home environment. ![]()
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